État de l’art : mesures de similarité sémantique locales et algorithmes globaux pour la désambiguïsation lexicale à base de connaissances (State of the art : Local Semantic Similarity Measures and Global Algorithmes for Knowledge-based Word Sense Disambiguation) [in French]

State of the art : Local Semantic Similarity Measures and Global Algorithmes for Knowledge-based Word Sense Disambiguation We present the main methods for unsupervised knowledge-based word sense disambiguation. On the one hand, at the local level, we present semantic similarity measures, which attempt to quantify the semantic proximity between two word senses. On the other hand, at the global level, we present algorithms which use local semantic similarity measures to assign the appropriate senses to words depending on their context, at the scale of a text or of a corpus. MOTS-CLÉS : désambiguïsation lexicale non-supervisée, mesures de similarité sémantique à base de connaissances, algorithmes globaux de propagation de mesures locales.

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